Articles

Nutrient Budgeting: An Enigma

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Nutrient budgeting seeks to quantify nutrient flows, evaluate the efficiency of current nutrient management practices, and provide recommendations to enhance sustainability and productivity. While fertilizer use is increasing, it’s often imbalanced, with a greater emphasis on nitrogen (N) and phosphorus (P) than potassium (K). The recommended NPK ratio (6.96:2.79:1 in 2019-20) differs significantly from the average crop uptake ratio (1.0:0.3:1.3). In the year 2000-2001, inorganic fertilizer was the dominant source contributing 64% of N and 78% of P inputs in Indian agriculture, whereas K input through inorganic fertilizer was 26%. The intrinsic complexity and diversity of nutrient dynamics across spatial and temporal dimensions, however, continue to make it an enigma. Numerous factors contribute to the difficulties in nutrient budgeting, such as uneven measuring techniques, variations in crop and soil properties, shifting weather patterns, and a lack of reliable field data. Furthermore, assumptions and models used to estimate nutrient flows—such as biological nitrogen fixation, leaching, gaseous losses, and crop uptake—frequently fail to account for site-specific reality. This complexity is further increased by human elements like inconsistent record-keeping and a variety of management techniques. However, by integrating field data, existing models, and literature-based nutrient coefficients, the studies in this field contributes to a deeper understanding of nutrient use efficiency and the potential for improving soil fertility management.

Influences of Historical and Anthropogenic Factors on the Dynamics of Reconstitution of Post-Cultivation Vegetation in the Sub-Sudanese Zone: The Case of the Department of Dianra, North-West Côte D’ivoire

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Prior knowledge of vegetation dynamics, including post-crop recovery dynamics, is necessary for rational and sustainable management of land assets. This study was initiated to assess the influence of historical and anthropogenic factors on post-cultivation reconstitution in the Dianra Department. To this end, information on the history and post-cultivation human activities was collected from farmers. The Phytoecological and dendrometric data were collected using the surface botanical method in the post-cultivation plots. In total, 105 plots of 400 m² were planted in post-cultivation plots between 1 and 32 years old. The influence of historical and anthropogenic factors was assessed using an Analysis of Covariance (ANCOVA), in which the functional traits of the species and the structural attributes of the plots were considered as the variables to be explained and the historical and anthropogenic factors as the explanatory variables. This analysis shows that post-cultivation reconstitution in the sub-Sudanese environment is subject to the influence of several factors, the most perceptible of which are: age, number of years of cultivation, grazed area, cultivation history, groundnut cultivation as the last crop, and cultivation technique by horse and cart. The age, groundnut cultivation as the last crop and the Open Forest/Wooded Savannah cultivation history favoured reconstitution. In contrast, a high number of years of cultivation, grazing and ploughing by horse and cart were unfavourable to reconstitution.

Mapping Spatiotemporal Dynamics of Akure Industrial Layout for Sustainable Development

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This research aimed at mapping the spatiotemporal dynamics of the Industrial Layout located in Akure Ondo State Nigeria. The dataset used are the administrative map of Ondo State, Akure Industrial Layout Boundary,various Landsat imageries of 32m resolution which are Thematic Mapper (TM) of 1986 & 1991, Enhanced Thematic Mapper Plus (ETM)+ of 2002, Operational Land Imager / Thermal Infrared Sensor (OLI/TIRS) of 2014, 2017, 2020; and Worldview 3 image 2020 of 1.24m resolution. The Landsat data were used to extract the different Land use/Land cover (LULC) within the study area. GPS receiver and Worldview 3 image were used to obtain the coordinates of the different LULC classes, which aided in the classification of image, and also for accuracy assessment of the classified image. All the Landsat standard data products were processed, to ascertain that they are free of radiometric and geometric errors using the Level 1 Product Generation System (LPGS) and extracted to obtain the landsat image bands. The extracted Landsat images (bands) were used in the processing and calculating the Normalized Difference Vegetation Index (NDVI) and calculation of LULC changes. Evaluation the accuracy of the results produced from the land cover classification was carried out by comparing the results of ground coordinates with the coordinates obtained from a higher resolution image (Worldview 3 image) in order to determine the accuracy of the land cover classification in the study area. The trend of changes of land cover in these areas was assessed and also, the prediction for the future condition both in terms of development was determined based on the results obtained from the initial results. Results from various maps produced and numerical data generated showed that Akure Industrial Layout was mainly dominated by shrub and grass land in 1986 and has in 34 years experienced transformation of 604% in the built environment (18% /year), 119% of Bareland (3.5%/year), and -29% of Grassland (0.9%/year), -66% of Shrub (2%/year). The forecast of the probable spatial extent for the years 2025 and 2030 were estimated to be 175.3Ha and 214.8Ha respectively, which shows there will be a continuous increase in the future development in Akure Industrial layout. The research recommended a proactive action from the government and end-users that will ensure a sustained manageability of the layout.